White paper: Reduce Bay Area Commuting 25%
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White paper: Reduce Bay Area Commuting by 25%“Fair Value Commuting” is a comprehensive, five-part solution to reduce SOV commuting from 75% to 50%: 1) enterprise commute trip reduction (ECTR) software, 2) mobility aggregation (MobAg) app, 3) “Similar-to-Stanford” revenue neutral workplace parking feebate, 4) fill commute “gaps” with better options, 5) reduce systemic obstacles to seamless mobility. White paper topics: a) 11 commute mode shift benefits, b) sparse evidence for commute reduction in auto-centered locations, c) “perfect storm” of state, regional and local policy demands 17% per-capita driving reduction, d) ideal ECTR + MobAg feature set, e) “gap-filling” includes e-bike/scooter, first/last mile, peer-to-peer instant carpooling, and bike stress reduction, f) autonomous vehicles increase driving and traffic, g) eight congestion pricing policies ranked on political viability and social equity, h) travel elasticity evidence reveals feebate efficacy, i) legislative path including a state bill, j) compelling business model and six-way win for key stakeholders.
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White paper as a series of comment-able Google docs organized in a Google sheet:
http://bit.ly/1QBMYnw
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Full PDF white paper. 193-pgs, 16MB, Aug 14, 2016 version:
http://www.cities21.org/wp.pdf
http://bit.ly/1SIfq8u
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Chapters 1-10 are the backbone of the white paper and run about 43 pages total.
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Google docs may be more current than the PDF
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Chapter / AppendixNAMEGoogle Drive Document DescriptionLink to Google Doc ChapterPress coverage
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1-10Reduce Bay Area Commuting by 25% via “Fair Value Commuting,” Chapters 1-101) It is difficult to reduce SOV commuting. 2) The Bay Area is very auto-centered. 3) There are only a few effective exceptions to suburban auto-centricity: 3A) Stanford charges $4 per day to park. 3B) Jobs for tech worker Millennials on top of high quality transit. 3C) $6,000 per worker per year “expensive but effective” TDM. 4) State, regional, and local public policy is building towards large mode shift. 4A) “Trip Caps” reduce SOV commuting. 4B) TDM and TMAs reduce SOV commuting. 5) Mobility Ecosystem, 6) ECTR combined with Mobility Aggregation, 7). ECTR case studies / gap filling examples, 8). Robotaxi/Robovan Future, 9) Ranking Congestion Pricing Policies, 10) Feebate Policy Detailsbit.ly/1n6nxiN Driverless Transportation: http://bit.ly/2afkD58 FastCompany article tooITS Intl Dec '15: http://bit.ly/1PxGAxy
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11Systemic Obstacles to Seamless Mobility1) Enable better public transit routes that cross county borders. 2) Public transit fare integration for multi-agency trips. 3) Create a series of commute shed maps, with gap analysis/filling. 4) If possible, modernize public transit electronic payment faster than scheduled. 5) Develop a healthy, interoperable smartphone mobility ecosystem with open APIs. 6) Begin a “supportive and safe” pricing discussion. 7) Adjust national pretax commute benefits law to favor green alternatives over SOV parking, 8) Standardized parking API, 9) reduce bike rider stress.http://bit.ly/1fFsVVT
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ASuburban Ridematch Needle in the Haystack ProblemProvided is a quantified explanation of the low ridematch probability of peer-to-peer (P2) on-demand ridematching {Lyft Carpool, WAZE RideWith, Scoop, Carma, Carzac, HOVee, NuRide, Ride.com, TwoGo, Slice Rides, RideAmigos, Duet, Split, and MüV} in car-loving portions of United States. On the surface, the concept of filling the many empty seats in cars has large potential to increase efficiency. Unfortunately, the probability of developing critical mass in car-loving areas is very challenging - the set of possible matches is distributed in a sparse manner. This challenge can be called the Needle in the Haystack Problem. Even making multiple optimistic assumptions, the match-making probability is small. In the Palo Alto calculation provided, within a 20-minute interval, only four out of 31,500 travelers can be matched. Additional challenges reduce the probability even further: 1) matchable travelers may not use the same service so may not be aware of each other, 2) the “Day 1 Challenge,” whereby new members do not all join on the same day and may quit a service before finding a match, 3) “driver backtracking shrinkage” where matches are prevented because picking up the potential rider entails a time penalty for the driver. Improvements are suggested. Scoop’s achievement of 0.6% Cisco commute mode share is detailed. 17 practitioner comments are provided, adding additional opinion and insight to the difficult challenge.http://bit.ly/1MtMdetCityLab 11/13/15: http://bit.ly/1MR6Rkl
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BSeasonable Reduction in Bike CommutesBike commuting provides a compelling user experience in nice weather, but what happens in the winter when it’s cold, rainy, and dark? Winter drop off: Lund (Sweden) 0%, San Francisco 20%, London 33%, Boston 40% Portland 43%, Seattle 44%, New York City 70%, Chicago 80%http://bit.ly/1WfNEU3 CityLab 1/26/16: http://bit.ly/1ouEsfy
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CSilicon Valley Commute Vector MapThe "cats cradle" or "string art fun" pattern increases the difficulty of providing effective SOV alternatives. This commute vector map shows how the messy suburban human settlement pattern is well-served by driving alone. 1) MTC’s activity-based travel demand forecasting model predicts travel flow throughout the nine-county Bay Area. One output is a “synthetic 2015 day” of trips taken by hour, travel mode, and trip purpose. Trips are between Travel Analysis Zones (TAZ). Most TAZ are small communities containing about 5,000 residents, so are about one-sixth the size of a zip code. There are 1454 TAZ. The synthetic day contains 23.8M trips taken by 7.4M persons. 2) “Silicon Valley” is defined as both Santa Clara County and San Mateo County. For commutes that are “contained” in Silicon Valley (where both home and work are in the area) there are 788,000 morning commutes. 3) A commute vector is a directional line beginning in the middle of a residential commute origination TAZ and terminating in a work commute destination TAZ. Pink commute vectors have 60-1200 commute trips. Pink circles represent employment centers. Smaller commute vectors of 40-59 trips are represented in orange. There are 1,102 pink vectors and 1404 orange vectors. bit.ly/1TK4iWC
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DWork/Live near Silicon Valley CaltrainSPUR's research shows very high (42%) transit commute mode share for those living and working within 1/2 mile of regional rail. How much of this is accounted for by San Francisco's auto-hostility? A large portion. For those living and working near Caltrain, excluding San Francisco stations, transit commute mode share is only 7%. http://bit.ly/1Y4QKaX
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EFreeway Robocars Induce DemandToyota: induces sprawl. Stanford's Sven Bieker: steals transit riders. Fehr & Peers paper: 25% robocar mkt share induces 10% more VMT. CA Air Resources Board: VMT increases because of rebound effect, sprawl, and mode capture from transitbit.ly/1Z8JsBy
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FFree-parked TDM LeadersLeaders: Google 52%, Genentech 58%, Facebook 59%, Microsoft – Redmond 60%, Apple 72%, Yahoo 75%. Also: Palantir & SurveyMonkey: 38%bit.ly/1ZQxMFQ
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GInternational/European MaaS InitiativesContent combed from the web and SlideShare: Europe: BMW, Daimler, Siemens, Bileto.cz, Finland national MaaS initiative, Euro MaaS initiative, Euro MobAg pilots: a) Vienna Smile, b) Montpellier (France) Project EMMA, c) Hannovermobil. International MaaS: Toyota Hamo. Looming worldwide competitors: Apple Siri, Google Now, Cortana faster-than-realtime with “calendar sniff,” will Lyft/Uber develop Enterprise CTR (commute trip reduction - part way there: Lyft for Work).http://bit.ly/20F2mnk
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HFeebate Efficacy Details41 TDM Case Studies from Best Workplaces for Commuters; Transportation Elasticities from VTPI; Moving Cooler report; Implementations by Stanford, 20th Century Corp, and CH2M Hill.bit.ly/1O9h13D
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IFeebate FAQbit.ly/1O7vrRI
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JSupporting Letters: Feebate and JVSV MaaS Project10 ECTR employer pilots, 22 partners, 9 supporters across the ecosystem {cities, agencies, employers, vendors, NGOs} http://bit.ly/1RehuVW
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KDraft bill: "Downward Sliding Trip Cap to Reduce Bay Area Congestion 25%"Within the last two years, the cities of Menlo Park, Mountain View, Sunnyvale, and Cupertino implemented “trip caps.” Implementation varies slightly between each city. These trip caps require anywhere from 30% to 66% SOV commute mode share. This bill uses the performance-based trip cap concept, with noncompliance triggering a "Stanford-style" commute program. http://bit.ly/1Qwaa62
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LRank 8 Congestion Reduction Policies - methodology & policy descriptionsIn order to reduce per-capita VMT, rank 8 or more congestion reduction policies on {political viability, GHG reduction, congestion reduction, cost-effectiveness, social equity, ease-of-implementation}. Suggested methodology: 1) How to quickly rank congestion reduction policies via the expert Delphi Method. 2) Guidance re political viability, weighting, and price elasticity of demand. 3) Description of 8 policies with impact forecast: A) $5/gal gas tax increase, B) $0.20/mi Road User Charge, C) Pay As You Drive auto insurance, D) Widespread job center $5 cordon entry charge, E) $5/day workplace SOV parking charge, F) $5 per day non-SOV incentive (“cashout”), G) $3.33/day SOV parking charge with non-SOV incentive (a “feebate”), H) San Mateo Highway 101 HOT3 + express bus + TDM. Guidance is provided for MPOs to scale this methodology into a formal, regional process.http://bit.ly/1PXW7YpCityLab 12/19/15: http://bit.ly/1NPtNUx
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MRecommendations for Political WranglingA recommended work scope for how an NGO can wrangle the political ecosystem to enact Fair Value Commuting. Includes recommendations for MTC/BAAQMD, cities, counties, state-level-actors, major employers, and developershttp://bit.ly/1O5iKEQ
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NBuilding entrance intercept surveysWhat are best practices for a “front door,” 100% response, mandatory clipboard intercept survey (using in-house staff) at an employer to collect commute mode and home zipcode? Assume one building with two levels of underground parking, a mix of commute modes, entrances, 400 employees, both visitors and employees enter during AM commute hours.http://bit.ly/1KWhHUK
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San Mateo County Hwy 101 - CTP2040 HOV4 Vision 1.Congestion pricing: PAYD + revenue neutral workplace parking feebate. 2. Performance-based mixed-flow lane conversion: 70% SOV => HOV2, 63% SOV => HOV3, 57% SOV => HOV4. 3. Gap filling - the impact of different modes improves over time.http://bit.ly/1Y9VhYV
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Related Project Documents
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Ranking spreadsheet for ranking congestion reduction policiesSummary plus ranking template sheets. 5 experts contribute rankings sorted first on political viability, and next on a weighted-average score on five dimensions: GHG reduction, congestion reduction, cost-effectiveness, social justice, and ease of implementation.
fill out
http://bit.ly/1RQdgmj
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MaaS Mobility Aggregation graphic4200x2400. Graphic's mention of "monthly discount" is more of an consumer-driving european concept and is not applicable to US enterprise/employer-driven TDM.http://bit.ly/1NYk9ih
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Fair Value Commuting Project: two-page project summaryFVC concept description with project work scope summaryhttp://bit.ly/FVCsummary
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Two-page Road-Congestion Pricing policy briefCalifornia / Bay Area Road/Congestion Pricing for GHG/Congestion Reduction. Barriers and opportunities. Practical strategies at local, regional, and state level.http://bit.ly/2bDY25o
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FTA MOD's two-page FVC briefFVC concept description with project work scope summaryhttp://bit.ly/FTA_FVC
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Two-page Fair Value Commuting policy briefFair Value Commuting (FVC) builds on the legal, institutional, and political base provided by SB375. FVC strengthens employer commute reduction programs. Stanford University’s commute program provides a starting point. Stanford charges SOV commuters for parking permits (equivalent to about $3.60/day SOV fee) and rebates that revenue to non-SOV modes including rail/bus transit, bike, and carpool. Stanford fills commute option gaps with private circulator bus, private line-haul bus, electric bikes/scooters, and on-demand rideshare. Stanford’s program reduced SOV commuting from 75% to 50%, eliminating the need for $107M in new parking structures.http://bit.ly/SOVpolicyBrief
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Stanford 1989 General Use Permit #12M square feet added with no new net trips. Noncompliance triggered intersection improvements.http://bit.ly/2aNlV9e
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2030 Transport VisionComprehensive (flawed) California 2030 ground passenger transport vision. Encompasses: Shared Electric Connected Autonomous (SECA) vehicles, less SOV, freeways, climate, public policy. . A starting point for discussion. http://bit.ly/2030transport
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Mobility ecosystem vendor mapSpreadsheet taxonomy encompassing: Moovel, Bridj, Scoop, Luum, Carma, Getaround, car2go, EcoReco, Motivate, ParkNow, etchttp://bit.ly/1IyZGhH
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3 Revolutions: pricing briefhttp://bit.ly/2bDY25o
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White paper formating
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Heading 1: Chapter title
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Heading 2: Section Heading within a Chapter
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Captioning: Arial, 8pt, italic
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Heading 6: footnote text
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